code: def _create_feature_extractor(model_name):
      from platform import system
      from ._internal_utils import _mac_ver
      from ._pre_trained_models import IMAGE_MODELS
      from turicreate import extensions
  
      # If we don't have Core ML, use a TensorFlow model.
      if system() != "Darwin" or _mac_ver() < (10, 13):
          ptModel = IMAGE_MODELS[model_name]()
          return TensorFlowFeatureExtractor(ptModel)
  
      download_path = _get_cache_dir()
  
      result = extensions.__dict__["image_deep_feature_extractor"]()
      result.init_options(
          {"model_name": model_name, "download_path": download_path}
      )
      return result
  
file_path: turicreate/src/python/turicreate/toolkits/_image_feature_extractor.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  from ._pre_trained_models import _get_cache_dir
  from turicreate._deps.minimal_package import _minimal_package_import_check
  import turicreate.toolkits._tf_utils
label_desc: Use image node_id 1 for calling a global function with example usage: _create_feature_extractor(model_name) and returns: result, TensorFlowFeatureExtractor